This guest post is authored by Greg McMillan.
In the ISA Automation Week Mentor Program, I am providing guidance for extremely talented individuals from Argentina, Brazil, Malaysia, Mexico, Saudi Arabia, and the USA. We will be sharing a question and the answers each week. If you would like to provide additional answers, please send them to Susan Colwell at ISA. The tenth question in the ISA Mentor program is from Danaca Jordan (USA):
“How can you tell if changing pressure in a pipeline is affecting your process control loop?”
While it is well known changes in pressure change the control valve flow, less recognized is the changes in the installed characteristic and the prevalence of pressure upsets. Liquid flow (unless there is flashing) through a control valve is proportional to the square root of the pressure drop across the valve. The installed characteristic changes as the ratio of the valve to total system drop changes. You can track down disturbances by finding what flow changed first (see “Tracking Down Disturbances”). If you don’t have a flow measurement for each control valve, it gets difficult. If there are multiple users of the stream, then a pressure change in the stream will cause coincident changes in the controller outputs of the users. If there is only one user of the stream with the pressure change, the first process controller output that starts to change was first affected by the stream pressure change either as a disturbance flow or manipulated flow. Different loop deadtimes can mess up this analysis depending upon disturbance type and path. Data analytics packages can determine correlations between process variables and flows but multivariate statistical process control assumes linear relationships and synchronization of inputs with outputs for continuous processes. Unmeasured disturbances, inputs that are valve positions (nonlinear installed characteristics) rather than flows, and process deadtime are problematic for applications in continuous operations. If you had wireless pressure transmitters, you could move them around to track down the source pressure changes. If you had secondary flow loops (see “Secondary Flow Loops Offer a Primary Advantage”, the question would go away because the flow loop would correct for the pressure change before it affected the primary process loop. Changes in stream temperature, composition, and density are also disturbances. If you don’t have measurements of these stream variables, you are relegated to identifying the first flow to be affected. Often a process controller changes a manipulated flow to counteract the stream changes. For ratioed flows (flow feedforward), the primary process controller adds a feedback correction for stream changes. Secondary flow loops are essential for flow feedforward.